Professor Yezzi was born in Gainsville, Florida and grew up in Minneapolis, Minnesota. He obtained both his Bachelor's degree and his Ph.D. in the Department of Electrical Engineering at the University of Minnesota with minors in mathematics and music. After completing his Ph.D., he continued his research as a post-Doctoral Research Associate at the Laboratory for Information and Decision Systems at Massachusetts Institute of Technology in Boston, MA. His research interests fall broadly within the fields of image processing and computer vision. In particular he is interested in curve and surface evolution theory and partial differential equation techniques as they apply to topics within these fields (such as segmentation, image smoothing and enhancement, optical flow, stereo disparity, shape from shading, object recognition, and visual tracking). Much of Dr. Yezzi's work is particularly tailored to problems in medical imaging, including cardiac ultrasound, MRI, and CT. He joined the Georgia Tech faculty in the fall of 1999 where he has taught courses in DSP and is working to develop advanced courses in computer vision and medical image processing. Professor Yezzi consults with industry in the areas of visual inspection and medical imaging. His hobbies include classical guitar, opera, and martial arts.

Erik I. Verriest received the degree of 'Burgerlijk Electrotechnisch Ingenieur' from the State University of Ghent, Ghent, Belgium in 1973, and the M.Sc. and Ph.D. degrees from Stanford University in 1975 and 1980, respectively. He was employed by the Control Systems Laboratory and the Hybrid Computation Centre, Ghent, Belgium, where he worked on process simulation and control in 1973-74. His doctoral research at Stanford was on the algebraic theory and balancing for time varying linear systems and array algorithms. He joined the faculty of Electrical and Computer Engineering at Georgia Tech in 1980. He spent the 1991-92, 1993-94 and 1994-95 academic years at Georgia Tech Lorraine. He has contributed to the application of the theory of systems over finite fields in cryptography, data compression, sensitivity analysis of array algorithms with applications in estimation and control, algorithms for optical computing. More recently he contributed to the theory of periodic and hybrid systems, delay - differential systems, model reduction for nonlinear systems, and control with communication constraints. He served on several IPC's and is a member of the IFAC Committee on Linear Systems.

Patricio Vela was born in Mexico City, Mexico and grew up in California. He earned his bachelor of science degree in 1998 and his doctorate in 2003 at the California Institute of Technology, where he did his graduate research on geometric nonlinear control androbotics. Dr. Vela came to Georgia Tech as a post-doctoral researcher in computer vision and joined the ECE faculty in 2005. His research interests lie in the geometric perspectives to control theory and computer vision. Recently, he has been interested in the role that computer vision can play for achieving control-theoretic objectives of (semi-)autonomous systems. His research also covers control of nonlinear systems, typically robotic systems.

Sam Coogan received the B.S. degree in Electrical Engineering from Georgia Tech and the M.S. and Ph.D. degrees in Electrical Engineering from the University of California, Berkeley. In 2015, he was a postdoctoral research engineer at Sensys Networks, Inc., and in 2012 he spent time at NASA's Jet Propulsion Lab. Before joining Georgia Tech in 2017, he was an assistant professor in the Electrical Engineering department at UCLA from 2015–2017. His awards and recognitions include the 2020 Donald P Eckman Award from the American Automatic Control Council recognizing "an outstanding young engineer in the field of automatic control", a Young Investigator Award from the Air Force Office of Scientific Research in 2019, a CAREER Award from the National Science Foundation in 2018, and the Outstanding paper award for the IEEE Transactions on Control of Network Systems in 2017.

Maegan received her Ph.D. in Mechanical Engineering (ME) from the California Institute of Technology (Caltech) in May 2023. Prior, she also received a M.S. in ME from Caltech in 2019 and a B.S. in ME from Georgia Tech in 2017. After graduating with her Ph.D., Maegan conducted a brief postdoc at Caltech (May–August 2023), followed by a brief research position at Disney Research (September–December 2023). Generally speaking, her research interests lie at the intersection of control theory and human-robot interaction, with specific applications towards lower-limb assistive devices. Much of her research is centered around the question: “What is the right way to walk?”. In her free time, Maegan enjoys puzzles, playing video games, and the piano.

Maegan Tucker joined Georgia Tech as an assistant professor with joint appointments in the School of Electrical & Computer Engineering and the School of Mechanical Engineering in January 2024.

Dr. Fumin Zhang joined Georgia Tech's School of Electrical and Computer Engineering in 2007 as an assistant professor. He received a Ph.D. degree in 2004 from the University of Maryland (College Park) in Electrical Engineering, and held a postdoctoral position in Princeton University from 2004 to 2007. His B.S. and M.S. degrees, both in electrical engineering, are from Tsinghua University in Beijing. Fumin Zhang's research focuses on mobile sensor networks that demonstrate bio-inspired long duration autonomy. He has contributed to the co-design of control, sensing, and communication algorithms for mobile sensing agents that collect information to model spatial temporal stochastic fields. An application domain of his research has been marine robots for environmental sensing and data collection. He has established a theoretical framework for the investigation of battery supported Cyber-Physical Systems. He also developed a co-design methodology for real-time scheduling, realtime control, and battery management. He is currently serving as the co-chair for the IEEE RAS Technical Committee on Marine Robotics and is the associate editor for IEEE Journal of Oceanic Engineering, Robotics and Automation Letters, IEEE Transactions on Automatic Control, and IEEE Transactions on Control of Networked Systems. He also serves as the deputy editor-in-chief for the Cyber-Physical Systems Journal.

Dr. Justin Romberg is the Schlumberger Professor and the Associate Chair for Research in the School of Electrical and Computer Engineering and the Associate Director for the Center for Machine Learning at Georgia Tech.

Dr. Romberg received the B.S.E.E. (1997), M.S. (1999) and Ph.D. (2004) degrees from Rice University in Houston, Texas. From Fall 2003 until Fall 2006, he was a Postdoctoral Scholar in Applied and Computational Mathematics at the California Institute of Technology. He spent the Summer of 2000 as a researcher at Xerox PARC, the Fall of 2003 as a visitor at the Laboratoire Jacques-Louis Lions in Paris, and the Fall of 2004 as a Fellow at UCLA's Institute for Pure and Applied Mathematics. In the Fall of 2006, he joined the Georgia Tech ECE faculty. In 2008 he received an ONR Young Investigator Award, in 2009 he received a PECASE award and a Packard Fellowship, and in 2010 he was named a Rice University Outstanding Young Engineering Alumnus. He is currently on the editorial board for the SIAM Journal on the Mathematics of Data Science, and is a Fellow of the IEEE.

His research interests lie on the intersection of signal processing, machine learning, optimization, and applied probability.

Russell D. Dupuis earned all of his academic degrees from the University of Illinois at Urbana-Champaign. He received his bachelor's degree with "Highest Honors-Bronze Tablet" in 1970. He received his master's in electrical engineering in 1971, and his Ph.D. in 1973. His alma mater has honored him with the University of Illinois Alumni Loyalty Award, and the Distinguished Alumnus Award. Dupuis worked at Texas Instruments from 1973 to 1975. In 1975, he joined Rockwell International where he was the first to demonstrate that MOCVD could be used for the growth of high-quality semiconductor thin films and devices. He joined AT&T Bell Laboratories in 1979 where he extended his work to the growth of InP-InGaAsP by MOCVD. In 1989 he became a chaired professor at the University of Texas at Austin. In August 2003, he was appointed Steve W. Chaddick Chair in Electro-Optics at Georgia Tech in ECE. He is currently studying the growth of III-V compound semiconductor devices by MOCVD, including materials in the InAlGaN/GaN, InAlGaAsP/GaAs, InAlGaAsSb, and InAlGaAsP/InP systems.

Professor Citrin earned a B.A. from Williams College (1985) and a M.S. (1987) and a Ph.D. (1991) from the University of Illinois, all in physics, where his dissertation was on the optical properties of semiconductor quantum wires. Subsequently, he was a post-doctoral research fellow at the Max Planck Institute for Solid State Research, Stuttgart, Germany (1992-1993) and Center Fellow at the Center for Ultrafast Optical Science at the University of Michigan (1993-1995). Dr. Citrin was an assistant professor of physics and materials science at Washington State University (1995 to 2001).

Professor Citrin joined the faculty at Georgia Tech in 2001 where his work focuses on terahertz technology and nanotechnology. He is a recipient of a Presidential Early Career Award for Scientists and Engineers and of a Friedrich Bessel Award from the Alexander Von Humboldt Stiftung. In addition, he is Project Coordinator on Nonlinear Optics and Dynamics at Georgia Tech-CNRS UMI 2958 located at Georgia Tech-Lorraine. Professor Citrin’s research in terahertz imaging is featured in the Georgia Tech press release, ”Imaging Technique Unlocks the Secrets of 17th Century Artists"; a list of some media placements from the press release may be found at http://photonics.georgiatech-metz.fr/node/33.

Research interests: 

• Terahertz nondestructive testing of materials
• Terahertz characterization of art and cultural heritage
• Chaos and nonlinear dynamics in external-cavity semiconductor lasers
• Nanophotonics
• High-speed electronic, photonic, and optoelectronic devices
• Nonlinear optical properties of semiconductor materials and devices